A predictive dialer is a system that generates outbound calls from a call center. Outbound calls that reach a live called party (i.e., a human being answers the call) are connected to call center agents for handling, i.e., servicing. Such answered calls for which no agent is immediately available to service them are referred to as nuisance calls. Nuisance calls are possible because the predictive dialer initiates calls without a priori assignment and connection of agents to the generated calls. Furthermore, because generated calls can go unanswered or may be answered by a machine as opposed to a live called party, the predictive dialer typically initiates more outbound calls than there are agents available to service them. With automatic call classification of whether or not, and by what, an outbound call has been answered, the call center determines the need for an agent only when the call is answered. The call center then attempts to match and connect the call answered by a live party to an individual agent for immediate servicing.
A call center has the conflicting objectives of minimizing agent idle time while minimizing the numbers of nuisance calls. But two characteristics of telephone calling are inherently problematic for agent utilization. The first is the long ring time required to reach a called party, and the second is a high incidence of call attempts that result in failure to connect to a live called party. Without predictive dialing, agents would spend considerable time waiting for ringing phones to be answered. When a ringing phone is not answered, the agent would have to wait again for results of the next call attempt. Predictive dialing attempts to reduce agent wait-times. However, reducing agent wait-times is not without the risk of connecting to a called party without an agent being available to service the call.
In a predictive dialing environment, agents are presently unavailable because they are performing tasks that are designated to be un-interruptible. That is, an agent can do only one task at a time and cannot start a new task until the previous task is completed. Additionally, only one agent can usually be assigned to a particular task. The tasks typically involve live clients in a transaction, and background fulfillment tasks may be dynamically interspersed amongst them. Agents that are presently handling tasks are rendered unavailable. However, each unavailable agent can be expected to complete his or her task with a particular probability over a future time interval.
Existing predictive dialers use various methods and algorithms to systematically initiate calls before agents are available to handle them. Whatever is the basic method that a dialer employs, it attempts to achieve a balance between agent utilization and nuisance-call rates. Such balancing typically employs heuristics realized in the predictive dialer's dialing algorithm. For example, a dialer may consider an agent available after the agent has spent a certain amount of time working a call, and initiate new calls depending on the dialer's hit rate. For instance, if the hit rate is 1/3, 3 calls will be initiated so that a live person can be expected to have been reached at about the time an agent is predicted to be available. Accordingly, predictive dialers have been oriented towards keeping agents busy. However, dialers face many dynamic and unsystematic variations in characteristics of the called population, characteristics of the calling campaign, spontaneous assignment of agents to other work, and inconsistent behavior of agents. These variations tend to upset any real balance between agent utilization and nuisance-call rates. The existing predictive methods do not sufficiently compensate for the unsystematic uncertainty in their predictive models. Either there is excessive agent idle time (detected as an excess service level), or there is lack of promptness in responding to called parties who answer (detected as an insufficient service level). A service level is a percentage or a ratio of those transactions out of all transactions that satisfy some criterion of “goodness.”
One technique used by predictive dialers has been to consider the probability that an agent will finish a task within a selected amount of time based on the amount of time that the agent has spent on a call the agent is presently handling. However, such systems fail to consider correlations that may exist between talk time and wrap-up time. For example, such systems may result in an unrealistically high probability that an agent will become available within a selected period of time when the agent's time in talk state becomes longer than normal. Other systems have simply considered the average time to advance in a wait queue, without consideration of the agents' states. Because of the deficiencies in previous systems, the consistent achievement of higher service levels (i.e. the avoidance of nuisance calls), for example 99% of calls made to a live person are connected to an agent that is immediately available, has been impossible.
As a result of increasing concern about nuisance calls, regulations attempting to prevent or limit the occurrence of such calls have been implemented. These regulations can impose fines for calls that are completed to a live person but that are not also immediately connected to an agent. At the same time, it remains important to keep agents busy. Therefore, it has become increasingly important to improve the accuracy of predictive dialers to avoid instances of nuisance calls while at the same time avoiding having agents idle.